code: def forward(self, pred: torch.Tensor, gt, mask):
      mask_sum = mask.sum()
      if mask_sum.item() == 0:
          return mask_sum, dict(l1_loss=mask_sum)
      else:
          loss = (torch.abs(pred[:, 0] - gt) * mask).sum() / mask_sum
          return loss, dict(l1_loss=loss)
  
file_path: EasyOCR/easyocr/DBNet/decoders/l1_loss.py
imports: import torch
  import torch.nn
label_desc: Use image node_id 2 for calling the MaskL1Loss obj's underlying member method code with example usage: obj.forward(pred, gt, mask) and returns: mask_sum,  dict, loss,  dict